[BioC] technical replicates

Naomi Altman naomi at stat.psu.edu
Sun Jan 11 16:03:58 MET 2004

I usually use mixed model ANOVA to determine differential expression.  By 
putting in a random effects term for sample (you have 2 technical reps per 
sample) you end up with the correct analysis.

However, in your case you have no sample replication.  As a result, you 
cannot do a statistically valid ANOVA.   People do use various 
approximations - the Affy-type Wilcoxon tests which treat the probes as 
replicates (makes me very very nervous); using the technical replicates as 
if they were biological replicates (makes me very nervous - there is no 
guarantee that there is much relationship between the technical and 
biological variation).  Of course, the best thing to do is to convince the 
investigators that biological replication is far more important than 
technical replication.  In most Affy studies, technical replication will 
not be cost-effective due to the relatively small technical variance and 
the large cost of individual arrays.

At 01:18 AM 1/9/2004, William Kenworthy wrote:
>Hi, I have just been passed a set of affy data that consists of 3
>states, two technical replicates of each state (6 chips overall)
>1. whats the best way (normalisations, algorithms) to leverage technical
>2. how do you tell algorithms such as rma which are the replicates?  (I
>presume the phenoData in the AffyBatch specifies this, but the examples
>are in a binary format so you cant open the raw data file and see how
>they are put together!)
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch

Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111

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